Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study
The models enabled accurate classification of HIBPV cases and highlighted key discriminative perioperative variables through SHAP-based interpretation. Intraoperative HR and BIS were significant contributing factors. Moreover, interactions between sevoflurane and age and between hypertension and calcium levels may inform individualized hemodynamic management strategies.
Authors
- Linwei Liu (ORCID: https://orcid.org/0000-0002-4028-631X)
- Yi Duan (ORCID: https://orcid.org/0000-0002-6229-9461)
- Zhifeng Gao (ORCID: https://orcid.org/0000-0001-6012-7466)
- Xiao Li (ORCID: https://orcid.org/0000-0002-7708-2193)
- Zheng Zhang (ORCID: https://orcid.org/0000-0001-6216-6872)
- Jian Wu (ORCID: https://orcid.org/0000-0002-7343-3777)
- Jinghan Wang (ORCID: https://orcid.org/0000-0003-3600-1243)
- Yaru Liu
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Chinese Academy of Sciences (CN)
- Institute of Computing Technology (CN)
- Beijing Tsinghua Chang Gung Hospital (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1080/07853890.2025.2537920
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00